Post on 15-May-2018
10 The relationship between university culture
and climate and research scientists’ spin-off
intentions
Annelore Huyghe & Mirjam Knockaert
Annelore Huyghe
University of Ghent
Tweekerkenstraat 2
9000 Gent, Belgium
Email: annelore.huyghe@ugent.be
Mirjam Knockaert
University of Ghent
Tweekerkenstraat 2
9000 Gent, Belgium
& University of Oslo
Centre for Entrepreneurship
Norway
Email: mirjam.knockaert@ugent.be
Abstract Over the past decades, universities have increasingly become involved
in entrepreneurial activities. Despite efforts to embrace their ‘third mission’, uni-
versities still demonstrate great heterogeneity in terms of their involvement in ac-
ademic entrepreneurship. This chapter adopts an institutional perspective to under-
stand how organizational characteristics affect research scientists’ entrepreneurial
intentions. We study the impact of university culture and climate on entrepreneur-
ial intentions, thereby specifically focusing on intentions to spin off a company.
Using a sample of 437 research scientists from Swedish and German universities,
our results reveal that the extent to which universities articulate entrepreneurship
as a fundamental element of their mission fosters research scientists’ spin-off in-
tentions. Furthermore, the presence of university role models positively affects re-
search scientists’ propensity to engage in entrepreneurial activities, both directly
and indirectly through entrepreneurial self-efficacy. Finally, research scientists
working at universities which explicitly reward people for ‘third mission’ related
output show higher levels of spin-off intentions. This study has implications for
both academics and practitioners, including university managers and policy mak-
ers.
A revised version of this article was accepted for publication in The Journal of Technology
Transfer; DOI 10.1007/s10961-014-9333-3.
INTRODUCTION
Universities do not only engage in research and teaching, but are increasingly ac-
tive in the commercialization of research results, or their so-called ‘third mission’
related to entrepreneurship and economic development (Etzkowitz 2003; Rasmus-
sen et al. 2006). This entrepreneurial tendency is inspired by decreasing university
budgets and pressure from policy makers who view the commercialization of re-
search as a key driver of national competitiveness (Ambos et al. 2008). ‘Third
stream’ entrepreneurial activities go beyond the traditional, scientific dissemina-
tion mechanisms, such as publications (Van Looy et al. 2011), and include univer-
sity spin-offs, patenting and licensing activities, contract research and consulting
(Wright et al. 2008).
As a result of the institutional transformation and universities’ growing interest
to fulfill their ‘third mission’, the academic literature has devoted considerable at-
tention to academic entrepreneurship. We refer to Rothaermel et al. (2007),
Markman et al. (2008) and Djokovic and Souitaris (2008) for excellent reviews of
the literature. In summary, the academic entrepreneurship literature includes stud-
ies at macro-level (studying the role of government and industry), meso-level (fo-
cusing on the university and the technology transfer office) and micro-level (stud-
ying firms and individual entrepreneurs) (Djokovic and Souitaris 2008). Only
recently, scholars have started to explore research scientists’ entrepreneurial inten-
tions (e.g., Mosey et al. 2012; Prodan and Drnovsek 2010). Entrepreneurial inten-
tions are considered the single best predictor of entrepreneurial behavior (Bird
1988; Fishbein and Ajzen 1975) and have been widely studied as outcome varia-
ble in diverse contexts (Krueger et al. 2000; Souitaris et al. 2007).
Studying entrepreneurial intentions in an academic context is important given
the presence of entrepreneurial potential in scientific knowledge (Obschonka et al.
2012). Academic research has been a crucial ingredient for the development of
new products and processes (Mansfield 1998) and about 70% of inventions re-
quire further involvement by the research scientist in order to be successfully
commercialized (Jensen and Thursby 2001). Academic entrepreneurship provides
a critical contribution of research scientists to the national economy and society
(Ping 1980) and is often considered crucial for competitive advantage (OECD
2003). Nevertheless, it is recognized that commercializing research results is diffi-
cult. At the heart of the problem is the inherent tension between academic and
commercial demands (Hackett 2001; West 2008). Universities have tried to over-
come this tension in a number of ways, for instance, by establishing technology
transfer offices (TTOs) (Siegel et al. 2007). Consequently, it may be valuable for
resource-constraint boundary spanners (such as technology transfer offices) to
identify those research scientists who are most likely to engage in entrepreneurial
activities in order to focus their attention on a specific target group.
So far, within the literature on entrepreneurial intentions, there is ample evi-
dence on individual drivers of entrepreneurial intentions (e.g., Dohse and Walter
2012; Lüthje and Franke 2003; Souitaris et al. 2007). Surprisingly, only few em-
pirical studies have explored the role of organizational drivers for entrepreneurial
intentions. Specifically, Lee et al. (2011) studied entrepreneurial intentions in a
corporate setting and Walter et al. (2011) assessed the extent to which characteris-
tics of university departments affect students’ self-employment intentions. Simi-
larly, the scarce research that has studied determinants of entrepreneurial inten-
tions in academia has mainly focused on the individual level. Prodan and
Drnovsek (2010) for instance found that entrepreneurial self-efficacy was the most
important driver of entrepreneurial intentions and found smaller effects related to
the type of research and the number of years the research scientist stayed at the in-
stitute. Goethner et al. (2012) showed that attitudes and perceived control were
key determinants of entrepreneurial intentions in an academic context, whereas
Obschonka et al. (2012) identified social identity as a central factor in explaining
entrepreneurial intentions. Strikingly, while it is vital to understand the context in
which the academic entrepreneur originates, to date, the organizational determi-
nants of research scientists’ entrepreneurial intentions remain an unexplored area.
Accordingly, this chapter aims at providing a better insight into the university
characteristics that affect research scientists’ propensity to engage in academic en-
trepreneurship. Specifically, we adopt an institutional perspective and focus on
university culture and climate as factors shaping research scientists’ intentions to
create a university spin-off (hereafter: ‘spin-off intentions’). Further, university
spin-offs are defined as new ventures initiated within a university setting and
based on technology derived from university research (Rasmussen and Borch
2010), and typically represent the central route to public research commercializa-
tion (Wright et al. 2008). We study our research question in a sample of 437 re-
search scientists from six Swedish and German universities.
This article unfolds as follows. We first present our conceptual framework
building on institutional theory, followed by a description of our research method-
ology. We subsequently present our results and discuss implications for academia,
practice and future research.
CONCEPTUAL FRAMEWORK
Institutional theory has been widely used as explanatory framework in diverse re-
search domains, ranging from marketing (e.g., Grewal and Dharwadkar 2002)
over strategic management (e.g., Peng et al. 2009) to entrepreneurship (e.g., Bru-
ton et al. 2010). Nevertheless, even among organizational theorists and sociolo-
gists, considerable variation exists in the definition of the central concepts of insti-
tution and institutionalization (DiMaggio and Powell 1983; Scott 1987).
This study approaches the organization as institution and draws upon a recently
emerging stream in institutional theory, called ‘new institutionalism’ (DiMaggio
& Powell 1983, 1991; Scott 1987, 2001; Zucker 1987). Viewing the organization
as an institution entails that implemented institutional elements generally arise
from within the organization itself or from imitation of similar organizations, not
from power or coercive processes located in the state (Zucker 1987). The neo-
institutional perspective rejects the rational-actor models of classical economics
and utilizes cognitive and cultural explanations of social and organizational phe-
nomena (DiMaggio and Powell 1991). Scott (2001, p.49) subsequently defines in-
stitutions as “multifaceted, durable social structures, made up of symbolic ele-
ments, social activities, and material resources”, with the central components of
institutions being rules (regulative), norms (normative) and values (cognitive). As
institutions’ rules, norms and values stipulate what is appropriate behavior, they
render some actions unacceptable or even beyond consideration (DiMaggio and
Powell 1991). Institutions are instrumental in shaping actors’ goals and beliefs
(Scott 1987) and in turn, affect motivational forces and behaviors (De Long and
Fahey 2000; Szulanski 1996).
Accordingly, we argue that the organizational context in which research scien-
tists are embedded might either trigger or restrain them from engaging in academ-
ic entrepreneurship, above and beyond individual-related characteristics. Despite a
growing number of initiatives targeted at the ‘third mission’, universities still
demonstrate large heterogeneity in their degree of institutional transformation
(Tijssen 2006) and in their support for and involvement in entrepreneurial activi-
ties (Kenney and Goe 2004; Louis et al. 1989; Wright et al. 2008). Universities
were traditionally developed to manage activities of research and teaching and, as
such, these institutions have to be adapted to incorporate academic entrepreneur-
ship. Universities hold distinct ideologies and trajectories towards their entrepre-
neurial role through which they exercise a strong influence on their members
(Stankiewicz 1986).
Following the above arguments, we propose that university characteristics in-
fluence the extent to which research scientists intend to undertake entrepreneurial
activities. In what follows, we focus on organizational culture and organizational
climate and develop a conceptual framework linking these university characteris-
tics to research scientists’ entrepreneurial intentions. Organizational culture and
climate are closely related, but distinct constructs (Kuenzi and Schminke 2009;
Schein 2000). Both constructs conceptualize the way people experience and de-
scribe their work environment (Schneider et al. 2013). However, on the one hand,
organizational culture may be defined as the beliefs and values that typify a setting
and are taught to new members as the proper way to think, feel, and act within the
organization (Schein 1985, Zohar & Hofmann 2012). On the other hand, the con-
cept of organizational climate designates how organizational policies, practices
and procedures embed beliefs and values, as such communicating the organiza-
tion’s goals and the means through which employees can achieve those goals (Os-
troff et al. 2003; Schneider et al. 1998). In other words, culture denotes assump-
tions, beliefs, meanings and values within an organization, whereas climate refers
to the practices through which culture is manifested (Denison 1996). We contend
that culture and climate constitute an integral part of the process of institutionali-
zation transformation, as academic entrepreneurship is not equally embedded or
formalized in all universities’ values and practices.
The relationship between organizational culture and spin-off
intentions
Adopting an institutional lens when examining culture is relevant (Zilber 2012), as
it represents one important means by which normative and cognitive structures are
transmitted (DiMaggio & Powell 1991). Organizational culture provides meaning
and context (Schein 1985) and affects how organizational members consciously
and subconsciously think and make decisions. Ultimately, organizational culture
has an impact on the way in which people perceive, feel and act (Hansen and
Wernerfelt 1989). Organizational culture shapes the way organizational members
set personal and professional objectives, perform tasks and administer resources to
achieve them. Within this study, we follow Schein (1985, p. 9)’s definition of or-
ganizational culture as “a pattern of basic assumptions invented, discovered or de-
veloped by a given group as it learns to cope with its problems of external adapta-
tion and internal integrations that has worked well enough to be considered valid,
and therefore, to be taught to new members as the correct way to perceive, think,
and feel in relation to those problems”. Subsequently, organizational culture, act-
ing through institutional belief systems and norms, can be a very effective means
of directing the attitude and behavior of organizational members towards entre-
preneurial activities.
Consequently, in order to increase research scientists’ interest in entrepreneuri-
al activities, universities could create a culture which is supportive towards such
activities, alongside investments in tangible organizational units such as technolo-
gy transfer offices, incubators and science parks. In this respect, Clark (1998) has
identified an integrated entrepreneurial culture as a core ingredient for successful
institutional transformations into entrepreneurial universities. Along the same
lines, O’Shea et al. (2005) argue that universities need to develop a culture sup-
portive of commercialization in order for academic entrepreneurship to flourish.
While there are numerous dimensions of organizational culture (Detert et al.
2000), this study examines two visible components of culture through which uni-
versities might influence research scientists’ intentions to engage in entrepreneuri-
al activities. Focusing on visible elements is appropriate, because organizational
culture is more likely to be transmitted to organizational members through visible
elements (values and behavioral patterns) than through invisible elements (basic
assumptions) (Hofstede 1998; Schein 1985). In particular, we focus on the pres-
ence of a university mission that incorporates academic entrepreneurship and role
models that exemplify academic entrepreneurship.
Entrepreneurial university mission
An organizational mission is a statement of the organization’s reason for being,
long term purpose and distinctiveness, reflecting the institutional beliefs systems
and ideologies (Klemm et al. 1991; Swales and Rogers 1995). The development of
an organizational mission is widely acknowledged to be a popular management
tool, which requires effective communication to both organizational members and
external stakeholders (Cochran and David 1986; Williams 2008). A large body of
research has indicated that an organizational mission guides the individual behav-
ior of organizational members (Bart 1996; Smith et al. 2001).
Historically, universities’ missions were primarily directed towards research
and teaching, turning their entrepreneurial transformation into a challenging task
(Ambos et al. 2008). Institutional change typically requires and implies a modifi-
cation of the culture or the key institutional elements that shape culture, including
the mission (Schein 1985). As indicated by Jacob et al. (2003), the reconciliation
of universities’ traditional and entrepreneurial activities does not only require
changes in infrastructure but also, amongst others, the adaptation of the university
mission. Ideally, an entrepreneurial university should focus on research, teaching
and entrepreneurial activities simultaneously (Etkowitz 2004; Guerrero and Ur-
bano 2012).
Following institutional theory and given the tendency of organizational mem-
bers to conform to organizational norms regarding entrepreneurship (Lewis et al.
2003; Peters and Fusfeld 1982), in particular in a university context (Friedman and
Silberman 2003; Roberts 1991), it is likely that the university mission will affect
research scientists’ entrepreneurial intentions. Accordingly, we argue that the
more universities highlight academic entrepreneurship as a fundamental part of
their mission, the greater research scientists’ intentions to engage in entrepreneuri-
al endeavors will be. Thus,
Hypothesis 1. The extent to which a university mission emphasizes academic
entrepreneurship compared to traditional activities is positively related to re-
search scientists’ spin-off intentions.
Entrepreneurial university role models
Role models constitute a second key element of organizational culture. The influ-
ence of role models on individuals has been highlighted in a number of contexts,
including marketing and consumer behavior (Childers and Rao 1992; Martin and
Bush 2000) and career development (Gibson 2003, 2004; Kram and Isabella
1985). Role modeling refers to a cognitive process in which individuals observe
attributes of people in social roles similar to themselves and increase this per-
ceived similarity by imitating these attributes (Erikson 1985; Gibson 2004). Indi-
viduals are affected by institutional norms, or behavioral patterns of peers within
their organization, and tend to act like them (Bercovitz and Feldman 2008; Haas
and Park 2010; Jain et al. 2009). Since research scientists are exposed to a peer-
oriented culture (Samsom and Gurdon 1993), the internalization or imitation of in-
stitutional norms is expected to be strong (Lewis et al. 2003).
Specifically, it is well acknowledged that role models and peers play a crucial
role in driving individuals’ entrepreneurial activity (Falck et al. 2012; Nanda and
Sorenson 2010; Thornton 1999). In a university context, the presence of entrepre-
neurial role models creates an example for research scientists and provides them
with a feeling of security. Peer examples signify that academic entrepreneurship is
accepted as a legitimate activity within the university, which reduces concerns
about the social repercussions of own entrepreneurial actions (Stuart and Ding
2006). The findings of Shane (2004) and Bercovitz and Feldman (2008) support
the view that research scientists’ commercialization decisions are socially influ-
enced.
Typically, individuals will imitate the particular behavior of their role models
(Bandura 1986). Indeed, Prodan and Drnovsek (2010) provided evidence on the
positive link between perceived role models of spin-off creation and research sci-
entists’ intentions to found a company themselves. Hence,
Hypothesis 2a. The presence of university role models involved in spin-off
creation is positively related to research scientists’ spin-off intentions.
Besides the direct impact of role models on entrepreneurial intentions through
internalization or imitation, we expect the presence of role models to also indirect-
ly affect entrepreneurial intentions, as a process of social comparison is likely to
take place. Individuals judge their own abilities by comparing themselves to simi-
lar others (Festinger 1954). The presence of entrepreneurial role models will con-
vince research scientists that they have what it takes to engage in entrepreneurial
activities themselves. Consequently, role models may influence entrepreneurial
self-efficacy, or an individual's confidence in his or her ability to successfully per-
form entrepreneurial roles and tasks (Chen et al. 1998). In turn, entrepreneurial
self-efficacy may affect entrepreneurial intentions. Boyd and Vozikis (1994) de-
veloped a theoretical model in which self-efficacy was proposed as an important
antecedent of entrepreneurial intentions. Empirical studies have provided strong
support for the existence of such relationship (Chen et al. 1998; Krueger 1993;
Chen et al. 1998; Zhao et al. 2005). Therefore, we assume that entrepreneurial role
models will indirectly, i.e. through entrepreneurial self-efficacy, affect spin-off in-
tentions. Thus,
Hypothesis 2b. Entrepreneurial self-efficacy mediates the relation between
university role models involved in spin-off creation and research scientists’
spin-off intentions.
The relationship between organizational climate and spin-off
intentions
Organizational climate is defined as the shared perceptions of and the meaning at-
tached to policies, practices and procedures that organizational members experi-
ence, as well as the kinds of behaviors that are expected, rewarded and supported
(Ostroff et al. 2003; Schneider et al. 1998). Climate reflects the tangible, culture-
embedding mechanisms of organizations, through which they attempt to direct the
energies of organizational members (Quinn and Rohrbaugh 1983; Schneider et al.
2013). Consequently, organizational climate is not identical, but closely related to
organizational culture. Climate represents how culture is manifested through or-
ganizational policies and procedures, and how the organizational environment is
perceived through the eyes of the individuals operating in that environment (Den-
ison 1996; Reichers and Schneider 1990). As part of the institutional context, or-
ganizational climate exerts a strong influence on organizational members’ motiva-
tion and behaviors (Brown and Leigh 1996; Kuenzi and Schminke 2009).
Therefore, organizational climate can also influence individuals’ attitudes and ac-
tions towards entrepreneurial activities.
Reward systems have often been seen as a focal dimension of organizational
climate (Schneider et al. 1998). Extant literature has shown how organizational
reward systems affect individual outcomes including motivation (e.g., Tyagi
1982), creativity (e.g., Shalley et al. 2004; Tesluk et al. 1997), job performance
and satisfaction (e.g., Downey et al. 1975), affective commitment (e.g., Rhoades
et al. 2001), knowledge sharing (e.g., Bartol and Srivastava 2002) and entrepre-
neurial behavior (e.g., Hornsby et al. 2002).
Entrepreneurial university reward system
Organizational rewards, be they monetary or non-monetary, reflect the organiza-
tion’s goals and objectives and encourage individual members to focus their atten-
tion on particular activities (Jensen 1993). Organizational members seek infor-
mation concerning what activities are rewarded by their institution, and direct their
behavior towards such activities while disregarding activities they are not reward-
ed for (Kerr 1975). Accordingly, through the implementation of specific reward
systems, organizations can enhance the likelihood that desired behaviors occur.
In a university context, reward systems are typically based on research scien-
tists’ publication output (Franklin et al. 2001). Nevertheless, scholars have sug-
gested that the establishment of rewards for entrepreneurial activities is needed in
order to foster a climate of entrepreneurship within universities (Friedman and
Silberman 2003; Shane 2004; Siegel et al. 2003). As such, if universities want to
encourage their employees to engage in research commercialization, it will be de-
sirable to adapt the incentive systems to the ‘third mission’ (Debackere and Veug-
elers 2005; Link et al. 2006; Markman et al. 2004). If reward systems are to stimu-
late research scientists to direct their efforts towards entrepreneurial activities,
they should no longer be exclusively based on research and teaching excellence,
but also reward entrepreneurial accomplishments (Henrekson and Rosenberg
2001; Jensen and Thursby 2001; Lockett and Wright 2005).
Following institutional theory and the literature on organizational reward sys-
tems, we can expect university rewards to affect research scientists’ entrepreneuri-
al intentions. Specifically, we argue that the more explicitly the university reward
system incorporates entrepreneurial activities as a criterion compared to the re-
wards for research and teaching, the greater the research scientist’s intentions to
engage in entrepreneurial activities. Thus,
Hypothesis 3. The extent to which a university reward system incorporates ac-
ademic entrepreneurship compared to traditional activities is positively related
to research scientists’ spin-off intentions.
Figure 1 summarizes our hypotheses.
Fig. 1 Conceptual model
H1 (+)
Entrepreneurial
role models
Entrepreneurial
mission
Entrepreneurial
reward system
Entrepreneurial
self-efficacy
Spin-off
intentions
H2a (+)
H2b (+) H2b (+)
H3 (+)
UN
IVE
RS
ITY
CU
LT
UR
E
UN
IVE
RS
ITY
CL
IMA
TE
RESEARCH METHODOLOGY
Data collection and sample
Our study is based upon unique cross-sectional data collected in 2012 at six uni-
versities in two European countries, Sweden and Germany. Both countries have
similarly strong and mature infrastructural support for entrepreneurial activities in-
itiated by both government and individual universities. Sweden and Germany are
characterized by high levels of R&D intensity and a relatively high degree of aca-
demic entrepreneurship (Wright et al. 2008). An important difference lies in the
academic exemption or professor’s privilege in Sweden, which asserts full owner-
ship of intellectual property rights to faculty (Klofsten and Jones-Evans 2000). For
both countries, we compiled a list of all universities using secondary data (includ-
ing reports by ministries of education, university rankings, technology transfer
networks and general internet searches). Next, we selected one or two geograph-
ical regions within each country (i.e. Gothenburg, Stockholm and Munchen re-
gion) and contacted all universities’ TTO through email or phone, which resulted
in full participation from 6 out of 15 TTOs contacted.
The data collection process included face-to-face interviews with technology
transfer officers from each university, followed by an online survey for research
scientists involved in different scientific disciplines. First, we contacted the tech-
nology transfer offices from the six universities (Chalmers University of Technol-
ogy, Gothenburg University, Mälardalen University, Halmstad University, KTH
Royal Institute of Technology and Technical University Munchen). Through face-
to-face interviews, we obtained information on university characteristics (e.g.,
human and financial resources, annual innovation output) and technology transfer
practices (e.g., history and organizational structure). Primary data were verified
and complemented with secondary data from annual reports, university and TTO
websites. Furthermore, we asked permission and assistance to contact research
scientists at each university. We specifically targeted research scientists (as op-
posed to, for instance, tenured professors) because research scientists (i.e. doctoral
and post-doctoral positions) are more likely to develop their career capital due to
uncertainty about which career track will be the most beneficial to them (Krabel
and Mueller 2009). In contrast, professors are typically more focused on establish-
ing their reputation in the scientific community.
The survey population consisted of 8,857 research scientists, of which 5,418 at
the Swedish universities and 3,439 at the German universities. Respondents re-
ceived a request through email to complete an online questionnaire. We obtained
1,103 failure messages indicating that email addresses were invalid or our mes-
sage could not be sent, resulting in a usable population of 7,754 research scien-
tists. After one week, a reminder email was sent. In total, 850 responses were re-
ceived (or 11% of the usable population). After elimination of incomplete re-
sponses, our final sample consists of 437 research scientists who fully completed
the questionnaire, or 5.6% of the usable population. T-tests revealed no significant
differences between respondents who filled in all questions and those who provid-
ed incomplete responses, or between early and late respondents, in terms of age,
gender, education, position, academic experience or country (p > 0.05). As such,
non-response bias was unlikely to be a problem in our dataset (Hair et al. 2006).
Some procedural techniques were used to reduce the risk of common method bias.
In our email, we guaranteed anonymity to reduce respondents’ tendency to give
socially desirable answers (Podsakoff et al. 2003). Moreover, careful attention was
given to the wording of questions in order to avoid vague concepts and to reduce
items’ ambiguity (Tourangeau et al. 2000).
Measures
Dependent variable
Spin-off intentions were measured by the following items: ‘How likely is it that, in
the foreseeable future, 1) You will engage in the founding of a university spin-
off?, 2) You will engage in the establishment of a company based upon an idea
and/or technology developed at the university? and 3) You will participate in the
founding of a firm to commercialize your research?’, on a scale ranging from 1
(very unlikely) to 7 (very likely). Scale reliability measured by Cronbach’s alpha
is 0.92.
Independent variables
University mission. Drawing upon Guerrero and Urbano (2012), we created 7
items to measure whether the university mission incorporates academic entrepre-
neurship. Respondents were asked to indicate their degree of agreement with the
following statements on a scale ranging from 1 (strongly disagree) to 7 (strongly
agree): ‘The mission of my university focuses on 1) Publishing papers with practi-
cal implications, 2) Knowledge transfer (patents, licenses, spin-offs), 3) Promoting
an entrepreneurial culture, 4) Generating entrepreneurs, 5) Publishing scientific,
peer-reviewed papers, 6) Academic excellence (research and teaching) and 7)
Consulting and contract research with industry.’ Exploratory factor analysis point-
ed to the existence of two factors: ‘focus on traditional activities’ (items 5 and 6;
Cronbach’s alpha 0.78) and ‘focus on entrepreneurial activities’ (items 1, 2, 3, 4
and 7; Cronbach’s alpha 0.84). Subsequently, we summarized these items in two
constructs and divided the values obtained for the first construct by the latter con-
struct. As such, our variable labeled ‘Entrepreneurial mission’ expresses the rela-
tive importance of ‘third mission’ within the university mission, as perceived by
the research scientists.
University role models. Participants were asked: ‘Has anyone in your universi-
ty, who you know personally, created a company based on university research?’.
Responses were coded 1 (41% of the sample) in case of perceived spin-off role
models and 0 otherwise. As such, a dummy variable was generated, labeled
‘Spin-off role models’.
University reward system. We created 6 items to reflect whether the university
reward system values academic entrepreneurship, beyond the traditional, scientific
activities of teaching and research. Using a 7-point Likert scale ranging from 1
(strongly disagree) to 7 (strongly agree), respondents were requested to answer the
following statements: ‘My rewards (e.g., salary, additional financial resources,
recognition from scientific community, flexi-time...) are determined by 1) Re-
search performance (e.g., number and quality of publications), 2) Involvement in
consulting and contract research, 3) Involvement in administrative, service or
committee activities, 4) Involvement in patenting and licensing, 5) Teaching per-
formance (e.g., student evaluations) and 6) Involvement in spin-off creation’. The
exploratory factor analysis revealed two factors: ‘emphasis on traditional rewards’
(items 1, 3 and 5; Cronbach’s alpha 0.70) and ‘emphasis on entrepreneurial re-
wards’ (items 2, 4 and 6; Cronbach’s alpha 0.88). We again generated summa-
rized measures for the two constructs and calculated the relative importance of en-
trepreneurial rewards compared to traditional rewards. The measure we obtained
was labeled ‘Entrepreneurial rewards’.
Other variables
Following prior literature on academic entrepreneurship and entrepreneurial inten-
tions, other characteristics could affect research scientists’ entrepreneurial inten-
tions. In what follows, we elaborate on our mediating and control variables.
Entrepreneurial self-efficacy was measured using the scale developed and vali-
dated by Zhao et al. (2005), including four items: ‘How confident are you in suc-
cessfully 1) Identifying new business opportunities?, 2) Creating new products?,
3) Thinking creatively? and 4) Commercializing an idea or new development?’ (1
= no confidence, 7 = complete confidence). Scale reliability measured by
Cronbach’s alpha is 0.81.
Gender (0 = male, 1 = female) was controlled for as men are usually more en-
trepreneurial than women (Crant 1996; Zhao et al. 2005).
Position (0 = doctoral researcher, 1 = post-doctoral researcher) indicates
whether the respondent has already obtained a PhD or not.
Technical degree (e.g., bio-science, physics, electronics, mechanics, robotics,
...) and non-technical degree (e.g., economics, law school, psychology, MBA, ...)
assesses the degree research scientists obtained (0 = no, 1 = yes). Education is a
key element of human capital which has been shown to affect the likelihood of be-
coming an entrepreneur (Mosey and Wright 2007; Shane 2000).
Academic experience indicates the number of years respondents have so far
spent in academia. Research scientists’ embeddedness in academia may lower the
likelihood of producing commercial outputs (Ambos et al. 2008).
Medicine was included as a dummy variable (coded 1 if a research scientist
performs research on clinical medicine or pharmacy, 0 otherwise), as medical in-
ventions have greater marketability than inventions from other disciplines (Powers
2003). Further, research scientists at medical faculties are typically more familiar
with working at the intersection of basic and applied research (Stuart and Ding
2006).
Country was controlled for, given the academic exemption or professor’s privi-
lege in Sweden (Klofsten and Jones-Evans 2000), by including a dummy variable
(0 = Germany, 1 = Sweden).
Discriminant validity and common method variance
Before testing our hypotheses, we ran confirmatory factor analyses to check the
distinctiveness of our measures (discriminant validity) and to rule out the impact
of common method bias. Discriminant validity was assessed for pairs of constructs
by constraining the estimated correlation parameter between constructs to 1 and
then performing a chi-square difference test on the values obtained from the con-
strained and unconstrained models (Anderson and Gerbing 1988). For all 10 pairs
of constructs, the chi-square values were significantly lower for the unconstrained
models (i.e. ∆ χ²df = 1 > 3.84), which indicates discriminant validity. Furthermore,
we wanted to verify whether our results were affected by common method vari-
ance, which is a legitimate concern when all variables are gathered through a
questionnaire (Podsakoff et al. 2003). Thus, we added a latent variable which was
allowed to influence all items of our base model in which all items were allowed
to load on their respective latent constructs. This additional latent variable repre-
sents the common method extracted from all items (Podsakoff et al. 2003). While
CFI and SRMR fit indices indicate that this model is somewhat better than the
model without common method variable, PNFI, which takes into account a mod-
el’s parsimony and hence helps compare models (Hair et al. 2006), was higher for
the model without the common method factor (0.75 versus 0.65), pointing to a bet-
ter model fit. This indicates that common method variance was not a major con-
cern in our study.
Table 1 Descriptive statistics and correlations
Variable Mean SD (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
(1) Gendera
0.41 0.49
(2) Positiona
0.25 0.43 0.05
(3) Technical degreea
0.62 0.49 -0.21** -0.14**
(4) Non-technical degreea
0.34 0.47 0.18** 0.14** -0.75**
(5) Academic experience 7.59 6.57 -0.06 0.36** -0.17** 0.16**
(6) Medicinea
0.21 0.41 0.18** 0.12** -0.31** 0.17** 0.19**
(7) ESE 3.80 1.27 -0.23** -0.08* 0.16** -0.14** 0.04 -0.12**
(8) Countrya
0.64 0.48 0.09* 0.12** -0.22** 0.24** 0.23** 0.31** -0.14**
(9) Entrepreneurial mission 0.83 0.33 -0.15** -0.09* 0.12** -0.12** -0.03 -0.17** 0.18** -0.11*
(10) Spin-off role models 0.41 0.49 -0.08 0.11** 0.10* -0.11** 0.11** 0.01 0.19** 0.01 0.05
(11) Entrepreneurial rewards 0.74 0.51 -0.08 -0.08 0.11* -0.17** -0.09* -0.03 0.21** -0.07 0.18** 0.13**
(12) Spin-off intentions 2.89 1.61 -0.17** -0.06 0.23** -0.16** -0.04 -0.08* 0.55** -0.02 0.23** 0.23** 0.27**
Pearson correlation coefficient (1-tailed): * p < 0.05, ** p < 0.01; n = 437 a Correlations of binary variables should be interpreted with care.
RESULTS
Table 1 provides the means, standard deviations and correlations for all variables.
Our sample consists of 281 (64%) Swedish and 156 (36%) German research scien-
tists. 41% of our respondents are women and 25% are post-docs. In addition, 269
(62%) research scientists in our sample possess a technical degree (science, tech-
nology or engineering) and 148 (34%) a non-technical degree (business, social
sciences or humanities). On average, respondents indicated having 7.59 years of
experience in academia (SD 6.57 years). 93 respondents (21%) are involved in
clinical medicine or pharmaceutical research.
Hierarchical OLS regressions were performed to evaluate the direct relation-
ships (Hypothesis 1, 2a and 3). In the first model, we entered only the control var-
iables, while the independent variables were added in the second model. We
checked for multicollinearity problems by calculating variance inflation factors
(VIFs) for all models. The highest VIF was 1.1, which is substantially below the
critical value of 5 (Hair et al. 2006) and indicates that multicollinearity is unlikely
to be a concern in our study. Our results are presented in Table 2.
Model 1 is the baseline model consisting of control variables only. Results in-
dicate that research scientists holding a technical degree (science, technology, or
engineering) have higher intentions to engage in spin-off creation (p < 0.01). Fur-
ther, in line with prior research (Prodan and Drnovsek 2010; Zhao et al. 2005), en-
trepreneurial self-efficacy positively affects research scientists’ entrepreneurial in-
tentions (p < 0.001). Finally, a significant country effect (p < 0.05) exists, with
Swedish research scientists showing higher intentions to found a company based
on university research compared to their German colleagues.
Models 2 presents the results for the direct effects of culture and climate on en-
trepreneurial intentions, whilst controlling for individual characteristics and coun-
try effects. In each of our full models, adding independent variables to the baseline
model leads to significant improvements of R² (p < 0.001). We find support for
Hypothesis 1, which proposed that the degree to which a university mission high-
lights academic entrepreneurship relative to its traditional tasks is positively asso-
ciated with research scientists’ spin-off intentions (p < 0.01). Hypothesis 2a,
which looked at the direct relationship between university role models and re-
search scientists’ entrepreneurial intentions, is also supported. The presence of
spin-off role models is positively related to spin-off intentions (p < 0.01). Our
findings also support Hypothesis 3, which states that the explicitness of academic
entrepreneurship as criterion in the university reward system, compared to re-
search and teaching, is positively related to research scientists’ entrepreneurial in-
tentions. Entrepreneurial rewards has a significant positive influence on spin-off
intentions (p < 0.001).
Table 2 OLS regression model coefficients (standard errors in parentheses)
* p < 0.05, ** p < 0.01, *** p < 0.001; n = 437
In order to test for the indirect relationship between university role models and
intentions through entrepreneurial self-efficacy (Hypothesis 2b), we used a macro
developed by Preacher and Hayes (2008). This allows us to disentangle the impact
of direct and indirect (mediaton) effects and relies on bootstrapping to test the me-
diation effect. The results are shown in Figure 2.
Spin-off intentions
Model 1 Model 2
Constant -0.206
(0.312)
-0.925**
(0.343)
Control variables
Gender -0.103
(0.136)
-0.05
(0.133)
Position 0.057
(0.158)
0.043
(0.154)
Technical degree 0.609**
(0.205)
0.627**
(0.199)
Non-technical degree 0.132
(0.205)
0.267
(0.201)
Academic experience -0.018
(0.011)
-0.018
(0.011)
Medicine 0.079
(0.173)
0.109
(0.169)
Entrepreneurial self-efficacy 0.687***
(0.052)
0.612***
(0.052)
Country 0.340*
(0.144)
0.342*
(0.140)
Independent variables
Entrepreneurial mission 0.576**
(0.195)
Spin-off role models 0.341**
(0.130)
Entrepreneurial rewards 0.409***
(0.127)
F-statistic 27.350*** 24.007***
R² 0.34 0.38
Adjusted R² 0.33 0.37
R² change 0.04***
Total effect = Indirect effect + Direct effect
= (a x b) + c
a b Bootstrap-indirect effect 95% CI
0.3794*
(0.2768)
0.6120***
(0.0523)
0.2322
(0.0809)
0.0870 – 0.4053
* p < 0.05, ** p < 0.01, *** p < 0.001; n = 437
F-statistic is significant at 0.1% level. Confidence interval (CI) is bias-corrected based on 10,000
bootstrap samples. Covariates included: gender, position, technical degree, non-technical degree,
academic experience, medicine,
Fig. 2 Diagram of the mediation effect
Figure 2 displays the significance of the indirect effects, in particular the extent
to which entrepreneurial self-efficacy mediates the relationship between university
role models and entrepreneurial intentions. The indirect effect of spin-off role
models on spin-off intentions via entrepreneurial self-efficacy is positive and sig-
nificant (95% CI = 0.087 – 0.405). This provides support for Hypothesis 2b.
Robustness checks
We conducted post hoc analyses to assess the robustness of our results and to pro-
vide more fine-grained insights into the impact of organizational culture and cli-
mate on research scientists’ entrepreneurial intentions. Specifically, while we de-
liberately assessed organizational culture and climate through the perceptions of
research scientists, it is relevant to verify the degree to which people within an or-
ganization agree in their perceptions (Schneider et al. 2013). We subsequently cal-
culated the (two-way random) intra-class correlation coefficients (ICCs) for the
responses received on the items for mission and reward system for each universi-
ty. ICC(2) is an index of the reliability of the group means and is commonly inter-
preted in line with other measures of reliability, with 0.70 or higher deemed ade-
quate (Bliese 2000; LeBreton and Senter 2008). All ICCs were significantly above
this generally accepted minimum value, with the lowest ICC equaling 0.89. This
c
a
Entrepreneurial role models Spin-off intentions
Entrepreneurial self-efficacy b
points to considerable convergence in the opinions of research scientists on the
university mission and reward system.
DISCUSSION AND CONCLUSIONS
This chapter has sought to contribute to our understanding of how organizational
culture and climate affect entrepreneurial intentions in academia, thereby adopting
an institutional perspective. Our study provides evidence that universities can
shape research scientists’ intentions to engage in spin-off creation, by offering an
institutional environment that promotes academic entrepreneurship. First, our
analyses reveal interesting insights into the influence of organizational culture on
entrepreneurial intentions. Particularly, the more universities emphasize academic
entrepreneurship in their mission compared to research and teaching, the greater
research scientists’ intentions to engage in spin-off creation. Furthermore, a se-
cond element of university culture, the presence of spin-off role models leads to
stronger intentions among research scientists to engage in spin-off creation. At the
same time, entrepreneurial role models also exert an indirect influence on entre-
preneurial intentions through an increase of research scientists’ entrepreneurial
self-efficacy. Specifically, research scientists who detect entrepreneurial role
models in their university feel more confident that they could successfully engage
in entrepreneurial activities themselves, and are therefore more likely to hold en-
trepreneurial intentions. Second, as for organizational climate, research scientists
working at universities which explicitly allocate rewards for entrepreneurial en-
deavors were found to possess higher levels of entrepreneurial intentions.
This study contributes to the academic literature in a number of ways. First, this
study contributes to the academic entrepreneurship literature, in which entrepre-
neurial intentions have only recently started to receive attention. Specifically, we
use an institutional lens to study the impact of organizational context on entrepre-
neurial intentions, while controlling for individual factors. Importantly, whereas
university culture has been identified as a key driver for academic entrepreneur-
ship (Clark 1998; Jacob et al. 2003, Martinelli et al. 2008; Siegel et al. 2004), to
this point no research has provided a theoretical framework nor empirical evi-
dence on the association between university culture and the development of entre-
preneurial intentions. As such, this research responds to recent calls by Djokovic
and Souitaris (2008) to untangle the impact of an entrepreneurial culture within
the university and by O’Shea et al. (2005) to explain academic entrepreneurship in
terms of university culture and rewards. Particularly, we show that elements of or-
ganizational culture, namely university mission and the presence of role models,
just as organizational climate, including the extent to which the university reward
system values entrepreneurial activities, have an important effect on research sci-
entists’ entrepreneurial intentions. Second, this chapter enriches the entrepreneuri-
al intentions literature which has predominantly focused on individual-level ex-
planations of entrepreneurial intentions, but has to a large extent neglected
organizational determinants. Given that individuals are embedded in institutional
contexts, they cannot be studied in an isolated manner. Accordingly, we respond
to a call by Dohse and Walter (2012) to contextualize entrepreneurial intentions.
Our research also has relevant implications for practitioners, including policy
makers and university management. First, for policy makers, who base university
funding upon evaluation criteria including a mix of research, teaching and entre-
preneurial activities (Etzkowitz et al. 2000), it may be useful to understand how
the universities they finance could enhance their commercialization output. Con-
sequently, for instance, they could help to increase this output by stimulating uni-
versities to include entrepreneurial activities as part of the reward system. Second,
for university management, this research shows that it is beneficial to incorporate
academic entrepreneurship in the university mission and to make sure that re-
search scientists are aware of existing role models. While examining the mecha-
nisms through which university management could communicate that entrepre-
neurship is a fundamental part of the university mission was beyond the scope of
our study, it is likely that any sort of communication (newsletters, speeches by
university management) that increases the awareness among research scientists of
the importance of entrepreneurial activities within their university will generate
higher levels of entrepreneurial intentions. Furthermore, university management
could ensure that role models make public appearances more frequently and as
such, focus research scientists’ attention on academic entrepreneurship as an on-
going and accepted organizational practice. Finally, university management could
establish a reward system that does not only value scientific output, but also dis-
tributes rewards for research scientists’ engagement in entrepreneurial activities.
Our study has a number of limitations which suggest fruitful areas for further
research. First, data were collected at six universities in Germany and Sweden.
While we find limited country differences based upon our analyses, there is little
reason to assume that our results could not be generalized to other regions in Eu-
rope. Yet, further research could broaden the geographical scope and develop sim-
ilar studies in other countries or study universities in a broader range of contexts.
Also, future studies could assess to which extent our results hold in samples of
public research institutions or university colleges. Second, while our results indi-
cate that raising awareness of an entrepreneurial mission or role models is condu-
cive to entrepreneurial intentions, our study does not provide insights into how
such awareness could be generated by universities and what communication
mechanisms yield the better result. Consequently, future research could explore
how to make research scientists optimally aware of the organizational culture in
order to direct their behavior towards entrepreneurial activities. Third, our data
collection is cross-sectional in nature. As such, we are unable to assess the impact
of changes in the university mission or reward system on entrepreneurial inten-
tions, nor to evaluate under which organizational conditions entrepreneurial inten-
tions actually translate into entrepreneurial behavior. We encourage future studies
to employ longitudinal research designs to shed light on these issues. Finally, this
chapter deliberately focused on institutional characteristics at the level of the uni-
versity. While we controlled for individual-level factors that have been found to
affect entrepreneurial intentions, future research could purposefully assess which
individual-level and organizational-level determinants reinforce each other, apply-
ing multilevel analysis techniques. Along the same lines, we call for research that
further disentangles the impact of institutional context on entrepreneurial inten-
tions, by including characteristics both at university and departmental level. Spe-
cifically, given that organizational culture may exist for a whole organization but
also simultaneously in the form of subcultures (Schneider et al. 2013), a strong en-
trepreneurial spirit at the institutional level without support from local levels
might have a less effective impact on research scientists’ entrepreneurial inten-
tions.
In spite of these limitations, to our knowledge, this chapter is the first to ad-
dress the impact of organizational characteristics on entrepreneurial intentions in
an academic context. Controlling for individual characteristics and considering ac-
ademic entrepreneurship in a broad sense, we found that university culture and
climate largely affect research scientists’ spin-off intentions.
Acknowledgments The authors would like to thank the interviewed technology transfer offic-
ers for their participation, as well as all respondents who completed the online survey. The first
author also gratefully acknowledges the financial support provided by Research Foundation
Flanders (FWO) in undertaking this research. We would further like to thank the organizers and
participants of the T2S Conference in Bergamo, November 2013, for their feedback on this chap-
ter.
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